TIME-OPTIMAL TRAJECTORY GENERATION FOR INDUSTRIAL ROBOTS BASED ON ELITE MUTATION SPARROW SEARCH ALGORITHM

Chunyan Li, Yongsheng Chao, Shuai Chen, Jiarong Li, and Yiping Yuan

Keywords

Trajectory planning, time optimal, non-uniform septic B-spline,elite mutation sparrow search algorithm (EMSSA) and constraintviolation

Abstract

To improve the efficiency and stability of industrial robots, a time-optimal trajectory planning method based on an elite mu- tation sparrow search algorithm (EMSSA) is proposed. First, a non-uniform septic B-spline interpolation trajectory function is con- structed, which overcomes the shortcoming of unsmooth joint ac- celeration or jerk in low-order interpolation and assigns kinematic parameters at the starting and stopping points. Second, the fitness function is constructed. It minimizes the sum of time intervals between two adjacent knots in B-spline trajectory considering kine- matic constraints. An EMSSA is proposed to schedule the time intervals and generate the time-optimal septic B-spline trajectory. Elite reverse learning strategy is used to optimize the initial popula- tion and accelerate the convergence speed of the algorithm. Besides, to enhance the solution quality and avoid falling into local optimiza- tion, the algorithm is improved by cosine-descending search step and normal-Cauchy mutation strategies. Furthermore, an example is given to verify that the proposed algorithm is effective in solving the time-optimal trajectory planning problem with multi-constraint and has the advantages of fast solving speed, high precision, and good robustness.

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